Psychometric evidence of a science, technology, engineering, and mathematics career interest survey of Indonesian high school students

The disparity between the growth of science, technology, engineering, and mathematics (STEM) job demand and students graduating from STEM areas raises an issue regarding the reason for low interest in STEM careers. An assessment tool is required to investigate this issue. However, the generalizabili...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Amalina Ijtihadi Kamilia
Vidákovich Tibor
Thwe Win Phyu
Dokumentumtípus: Cikk
Megjelent: 2025
Sorozat:SCIENTIFIC REPORTS 15 No. 1
Tárgyszavak:
doi:10.1038/s41598-025-92587-4

mtmt:36054103
Online Access:http://publicatio.bibl.u-szeged.hu/36403
Leíró adatok
Tartalmi kivonat:The disparity between the growth of science, technology, engineering, and mathematics (STEM) job demand and students graduating from STEM areas raises an issue regarding the reason for low interest in STEM careers. An assessment tool is required to investigate this issue. However, the generalizability of existing assessment tools to be conducted cross-culturally becomes a concern. This study aims to report the psychometric evidence of the STEM career interest survey (STEM-CIS) in the Indonesian context using a quantitative design with a stratified random sampling technique. Data from 738 high school students were analyzed using confirmatory factor analysis (CFA). The adapted STEM-CIS showed good psychometric evidence as a single measure, a discipline-specific measure, and a social cognitive career theory (SCCT)-specific subscale measure. The reliability values of the adapted STEM-CIS indicated high, confirming its robustness for assessing STEM career interest among Indonesian high school population. These findings support the use of the adapted STEM-CIS as a contextually relevant and validated tool for cross-cultural research on STEM career interest. This study contributes to the global need for culturally adaptable assessment tools.
Terjedelem/Fizikai jellemzők:13
ISSN:2045-2322